INTEGRATING DATABASES AND WORDNET FOR SEMANTIC SEARCH

dc.contributor.authorZUBAIRU, ABUBAKAR HUSSAINI
dc.date.accessioned2017-07-18T08:01:09Z
dc.date.available2017-07-18T08:01:09Z
dc.date.issued2014-09
dc.descriptionA THESIS SUBMITTED TO THE SCHOOL OF POSTGRADUATE STUDIES, AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILMENT FOR THE AWARD OF MASTER DEGREE IN COMPUTER SCIENCE DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE AHMADU BELLO UNIVERSITY, ZARIA NIGERIAen_US
dc.description.abstractSemantic integration of heterogeneous databases requires that user queries are understood semantically and can be related to the real contents of underlying databases. The state of art on data integration is focusing on using ontologies which is described as a formal and explicit conceptualization, as a semantic foundation for data integration. Unlike the previous research that considered the databases to have a well structured ontologies, this thesis employs WordNet lexical database to mine for synonyms from WordNet synsets into cluster. A query reformulation algorithm is proposed to reformulate the user query based on the retrieved synonyms and then lookup for all the queries in the database(s). The implementation turned out to be effective in practical applications, with a particular set of data, as the system is able to identify terms correctly based on synset, while previous methods relying only on available terms in the WordNet, this thesis can handle an unknown term by the WordNet by inserting new term into the existing synset in the WordNet database. Though, the evaluation results show that the proposed approach improves recall, but the system incurs high execution time as the number of table increases.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/9080
dc.language.isoenen_US
dc.subjectINTEGRATING DATABASES,en_US
dc.subjectWORDNET,en_US
dc.subjectSEMANTIC SEARCH,en_US
dc.titleINTEGRATING DATABASES AND WORDNET FOR SEMANTIC SEARCHen_US
dc.typeThesisen_US
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